Post on 24-Feb-2016
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The Housing Market across the Greek Islands
Dimitra KavarnouUniversity of Reading
d.kavarnou@pgr.reading.ac.uk
Dimitra Kavarnou - Henley Business School, University of Reading
A bit more of Geography…
Dimitra Kavarnou - Henley Business School, University of Reading
A bit more of Geography…
•>than 6,000 islands/isles•117 inhabited islands•79 islands >100 (population)•53 islands>1,000
Dimitra Kavarnou - Henley Business School, University of Reading
Ionian IslandsSporades Islands
Argo Saronic Islands
Cyclades Islands
North East Aegean Sea Islands
Dodecanese Islands
Dimitra Kavarnou - Henley Business School, University of Reading
Size…Group Number of
Islands in this Research
Population Geographical Size (m2)
Ionian Islands 5 203,210 2,200North East Aegean Sea Islands
5194,820 3,685
Argo – Saronic Islands
3
45,270 167Sporades Islands 4 16,700 417.5Cyclades Islands 11 108,370 1,947.36Dodecanese Islands 8 185,950 2,345Total 36 754,320 10,761.86
Dimitra Kavarnou - Henley Business School, University of Reading
Attributes of the Housing Market - I
1. Heterogeneity• Heterogeneity in many levels
Property/ Neighbourhood/ Settlement (Villages/towns)/ Islands/ Groups of Islands
• Housing SubmarketsIslands – Groups of Islands
2. Durability• Community formation (trade/ piracies/ occupations/
wars)• Horizontal ownership (bequests)• Ownership rate 80% - Cultural Aspect• Financial Course
Booms and Recessions
Dimitra Kavarnou - Henley Business School, University of Reading
Attributes of the Housing Market - II3. Political Economy
• Plethora of laws/ rules/ regulation• Tax Regime continuously changing –
Unstable• New Laws and additional taxation
established and applied from 01-01/2014• Taxation constitutes a Disincentive to be a
homeowner – investor4. Transactional Costs• High Transaction Costs• Among the highest in EU
Dimitra Kavarnou - Henley Business School, University of Reading
Attributes of the Housing Market - III
5. Imperfect Information• Lack of an well-organised information institution• Insufficient National Cadastre• The area of the islands is not mapped• Competitive, unprofessional, non-accredited
brokerage industry6. Immovability• Any real estate/housing market is immovable• Increased demand for spatial development
(amenities, infrastructure, employment, etc.)• More evident to islands which have physical
boundaries
Dimitra Kavarnou - Henley Business School, University of Reading
Attributes of the Housing Market – IV
7. External EffectsMain focus on the heterogeneity in island/
group of islands level: the public amenities (Presence of public
amenities on the islands/ distance from properties)
• Port (distance)• Hospital (presence)• Airport (presence and distance)• University (presence) Tourism rate Luxury rate Density (population/ geographical size)
Dimitra Kavarnou - Henley Business School, University of Reading
Hedonic Research: Idea• This research assesses and analyses the variables
that compose the house prices in the islands of Greece
• This research examines the impact/ significance of local public amenities on house prices across 36 islands of Greece
• The model controls for several structural and locational characteristics of the properties as well as economic and demographic attributes of the islands
Dimitra Kavarnou - Henley Business School, University of Reading
Methodology - I• Hedonic Regression Method (The method that decomposes the dependant variable under the scope into its constituent characteristics, and obtains assessments of the contributory value of each specific characteristic)(Rosen; 1974, Roback;1982, Bajari and Benkard; 2005)
In this research, the dependant variable (Y) is the Assessed Housing Prices - AHP or P for every property (i) , island(j), group of island(k)
Pi,j,k = α + ∑β Xi,j,k + εi,j,k
In order to mitigate the problem of heteroskedasticity as well as to compare percentage-wise the effect on the Assessed Housing Prices
(1) log(Pi,j,k)= α + ∑β Xi,j,k + εi,j,k
Υi = α + β1Χ1 + β2Χ2 + …+ βi Xi + εi
Dimitra Kavarnou - Henley Business School, University of Reading
Methodology - IIBut Τhere are also island characteristics for each island (j):
(2) log(Pi,j,k) = α + ∑β Xi,j,k + ∑γZj,k + εi,j,k
Controlling the Fixed Effects for each island:(3) log(Pi,j,k) = α + ∑β Xi,j,k + δj + εi,j,k
(Boundary fixed effects model: Black;1999, Clapp, Nanda and Ross; 2008)where δ is the total unobserved effects for each island (j) - dummies
Dimitra Kavarnou - Henley Business School, University of Reading
Data - I1. Two files from the Bank of Greece including properties in the islands that have been evaluated from 2005-2013 with property characteristics:
The property characteristics (Xi,j,k) included are:• Some details about the property location (not exact)• The living space (m2)• The land area (m2)• The date/year of permit, completion, evaluation• The property type (flat/detached house/ maisonette) and
the floor• Some information about the construction quality, the
neighbourhood, the view (limited) • Some information about the store rooms and the parking
spaces
file 1 11,553file 2 3,384
Total 14,937 pr.
Data - IILimitations of the dataset• Not exact location (address/number, to many cases
only local toponyms of settlements) Either because of incomplete dataset from the
estimatorsBut Mainly because the properties in the Islands do not
have an address themselves but they refer to the closest village/settlement
With this very limited information about their location, it was VERY difficult and time-consuming to spot the properties and calculate their distances from the amenities (ports/airports)
• Lots of missing/ incomplete values from the evaluators (view, land, year of completion/permit)
Dimitra Kavarnou - Henley Business School, University of Reading
Dimitra Kavarnou - Henley Business School, University of Reading
Data - III• Data Set Cleaning:Out of the 14,937 properties I received, I excluded:- 3,620 properties in Evvoia and Crete (separate analysis – research)- 850 approx. duplications- 500 approx. did not concern properties on islands (incorrect entries)- 3,000 approx. to which the land area was not available - 300 approx. to which the year of completion or the year of permit was
not available (not able to calculate the age of the property) - 300 approx. concerned islands with population<1,000p. or islands with
insufficient number of observations/island (<15) 6,350 properties approx. in 36 islands to be spotted and calculated- 2,000 properties approx. not able to spot/ find the approx. location of the closer village in Google Earth/ Google maps 4, 369 properties spotted in the final dataset
Dimitra Kavarnou - Henley Business School, University of Reading
Data - IVSpotting the properties in Google Earth (approximately)
Dimitra Kavarnou - Henley Business School, University of Reading
Data - V
Dimitra Kavarnou - Henley Business School, University of Reading
Data - VI
Calculating time distances in Google mapsto port: to airport:
Dimitra Kavarnou - Henley Business School, University of Reading
Data Analysis - II
•
Dimitra Kavarnou - Henley Business School, University of Reading
Data Analysis - III• Deflation of Assessed Housing PricesThe Prices are deflated and expressed in December 2012 prices:
where:HICPDec2012= 123.28HICPt = the HICP of the month year of the evaluation(Source of the HICP tables: Hellenic Statistic Authority)
• Dummy Variables Xi,j,k for the property types:
- Flat- Detached House- Maisonette
Data Analysis - IV• Dummy Variables (Zj,k) for controlling:- The Presence of Airport on the island- The Presence of Prefectural General Hospital on the island- The Presence of University on the island
• Dummy Variables (δj) for the fixed effects - controlling the unobserved heterogeneity of the islands (one dummy for each island)
• Dummy Variables (Xi,j,k) for controlling:• View (whether the property has view to the sea or not)• Proximity to Capital (whether the property is located in
the island’s capital or not)• Coastal Settlement (whether the property is located in a
coastal settlement or not)Dimitra Kavarnou - Henley Business School,
University of Reading
Dimitra Kavarnou - Henley Business School, University of Reading
Descriptive Statistics – of the Groups 1. Ionian Islands 1. North-East Aegean Islands 1. Sporades Islands
Variable N Mean Median SD N Mean Median SD N Mean Median SD
Assessed Values 980
363,409 208,389 201,879 848
219,071 166,450 189,111 232
287,149 236,294 257,949
Living Space 980
139 119 90 848
131 113 112 232
149 119 157
Land 980
1,061 313 2,373 848
636 131 1541 232
2080 517 6890
Age 980
14 6 18 848
30 23 22 232
19 11 22
Tourism(1000s) 980
25.0271 0.0420 43.6460 848
6.0631 0.9480 9.6050 232
- - -
Density(1000s/m2)
980
0.1041 0.0331 0.1707 848
0.0566 0.0330 0.0688 232
0.0437 0.0141 0.1273
1. Argo-Saronic Islands 1. Cyclades Islands 1. Dodecanese Islands
Variable N Mean Median SD N Mean Median SD N Median SD
Assessed Values 355
325,058 251,804 258,350 966
434,331 290,441 830,450 988
237,470 196,683 191,292
Living Space 355
137 120 75 966
147 119 108 988
124 103 93
Land 355
536 304 944 966
1733 352 3841 988
707 133 2162
Age 355
8 8 4 966
17 8 24 988
20 19 13
Tourism(1000s) 355
- - - 966
4.3298 0.1630 11.8380 988
50.9470 0.4590 85.6460
Density(1000s/m2)
355
0.3371 0.0396 0.4128 966
0.0898 0.0135 0.2544 988
0.0939 0.0135 0.1504
Results OLS - GroupsDependent Variable: LOG(REAL_ASSESSED_VALUES)
Variables (Xi,j,k) Ionian Islands North East Aegean Islands
Sporades Islands
ArgoSaronic Islands
Cyclades Islands
Dodecanese Islands
C 10.35***(81.62)
8.23***(48.10)
9.34***(25.64)
9.00***(28.42)
8.94***(72.85)
8.41***(45.56)
Log(Living_Space) 0.67***(20.75)
0.80***(19.15)
0.61***(7.73)
0.70***(11.35)
0.71***(20.32)
0.68***(17.85)
Log(land) 0.13***(6.45)
0.04*(1.68)
0.03(0.73)
0.13**(2.05)
0.05**(2.33)
0.17***(6.89)
Age -0.004***(-5.40)
-0.005***(-9.19)
-0.006***(-3.87)
-0.005***(-4.16)
-0.005***(-7.82)
-0.005***(-7.58)
t2 -0.21***(-7.69)
-0.16***(-5.93)
-0.121*(-1.84)
-0.16***(-3.29)
-0.11***(-3.68)
-0.10***(-3.88)
t3 -0.007(-0.11)
0.25***(5.66)
-0.053(-0.35)
-0.24*(-1.76)
0.03(0.40)
0.02(0.31)
PUR 0.0004(0.94)
-0.001***(-3.01)
-0.001(-1.59)
-0.0002(-0.21)
-0.0006(-1.17)
0.002***(3.05)
Floor 0.01(0.65)
-0.006(-0.62)
0.056(1.29)
0.06**(2.00)
0.002(0.22)
-0.02(-1.51)
View 0.25***(5.41)
0.22***(5.92)
0.07(0.95)
0.252***(4.90)
0.22***(7.45)
0.17***(5.55)
Presence_Hospital 1.04***(13.02)
--
- 0.04(0.58)
0.42*(1.88)
Presence_University - 0.13(1.25)
- - -0.171(-0.59)
-0.21***(-3.48)
Presence_Airport -2.39***(-30.69)
- 0.009(0.14)
- -0.007(-0.14)
-0.50***(-4.42)
PtCapital 0.21***(5.32)
0.04(1.27)
0.03(0.45)
0.071(1.53)
0.05(1.50)
0.06*(1.93)
Coastal_Settlement 0.03(0.88)
0.10***(2.69)
0.05(0.61)
0.11(1.10)
0.07**(2.34)
0.08***(2.80)
Tourism 0.16***(32.76)
0.001(0.21)
- - -0.03(-1.46)
-0.02***(-9.16)
Luxury 0.36***(16.06)
-0.06(-1.63)
- - 0.37***(8.09)
0.09***(36.11)
Density -56.26***-26.33)
-1.24(-0.80)
1.46(1.60)
-2.05***(-9.76)
-0.02(-0.02)
-3.59**(-2.07)
R2 0.63 0.68 0.52 0.67 0.68 0.71
N 975 844 231 353 958 965
Dimitra Kavarnou - Henley Business School, University of Reading
Results Fixed Effects- Groups
Dimitra Kavarnou - Henley Business School, University of Reading
FIXED EFFECTS Ionian Islands North East Aegean Sea
Islands Argo – Saronic Islands
Sporades Islands Cyclades Islands Dodecanese Islands
(1) (2) (3) (4) (1) (2) (3) (4) (1) (2) (1) (2) (3) (4) (1) (2) (3) (4) (1) (2) (3) (4) R-sq 0.594 0.629 0.588 0.618 0.656 0.686 0.657 0.687 0.674 0.702 0.530 0.539 0.459 0.473 0.664 0.696 0.729 0.754 0.690 0.706 0.699 0.720 N 977 975 799 797 844 844 844 844 355 353 232 231 99 99 962 958 581 578 988 965 871 848 C 8.428***
(269.97) 8.444*** (91.12)
8.422*** (152.15)
8.438*** (52.44)
8.282*** (49.01)
8.349*** (93.42)
8.294*** (52.37)
8.363*** (94.66)
8.400*** (37.80)
8.630*** (40.27)
9.214*** (28.41)
9.166*** (40.51)
9.612*** (92.12)
9.482*** (37.25)
8.978*** (50.26)
8.979*** (54.54)
8.852*** (40.25)
8.950*** (44.49)
8.087*** (38.54)
8.080*** (38.88)
8.105*** (32.40)
8.133*** (35.51)
log_ls 0.666*** (13.18)
0.647*** (12.45)
0.667*** (9.32)
0.651*** (8.29)
0.819*** (12.27)
0.788*** (15.69)
0.820*** (12.05)
0.791*** (15.62)
0.762*** (22.16)
0.722*** (20.65)
0.637*** (14.58)
0.607*** (9.93)
0.555*** (44.66)
0.516*** (213.34)
0.727*** (15.07)
0.701*** (16.02)
0.729*** (12.08)
0.685*** (13.49)
0.709*** (23.84)
0.686*** (23.88)
0.730*** (20.49)
0.706*** (21.29)
log_land
0.144*** (4.49)
0.142*** (6.02)
0.140*** (3.46)
0.139*** (4.18)
0.054* (1.67)
0.044 (1.51)
0.053 (1.60)
0.042 (1.42)
0.124* (1.78)
0.098 (1.32)
0.035** (2.25)
0.046*** (4.01)
0.064*** (32.41)
0.070** (2.45)
0.0526** (2.42)
0.046** (2.03)
0.066** (2.27)
0.058* (1.82)
0.153*** (5.23)
0.160*** (5.34)
0.132*** (4.61)
0.138*** (5.10)
age -0.004*** (-3.71)
-0.004*** (-3.80)
-0.004*** (-5.31)
-0.005*** (-7.57)
-0.006*** (-9.36)
-0.005*** (-7.35)
-0.006*** (-9.37)
-0.005*** (-7.44)
-0.006** (2.23)
-0.006*** (-2.65)
-0.005*** (-4.57)
-0.006*** (-4.74)
-0.007*** (-19.78)
-0.007*** (-3.91)
-0.006*** (-5.18)
-0.005*** (-4.77)
-0.006*** (-6.71)
-0.005*** (-6.70)
-0.005*** (-4.17)
-0.005*** (-3.80)
-0.006*** (-4.35)
-0.005*** (-3.79)
t2 -0.201*** (-4.35)
-0.198*** (-6.15)
-0.193*** (-5.21)
-0.188*** (-8.04)
-0.190*** (-3.41)
-0.158*** (-2.63)
-0.191*** (-3.41)
-0.160*** (-2.62)
-0.131*** (-7.33)
-0.142*** (-8.17)
-0.112 (-0.81)
-0.112 (-0.80)
-0.319*** (-6.87)
-0.303*** (-5.00)
-0.155** (-2.17)
-0.113 (-1.49)
-0.104** (-1.96)
-0.040 (-0.85)
-0.087*** (-4.77)
-0.079*** (-4.37)
-0.074*** (-4.17)
-0.069*** (-4.21)
t3 -0.042 (-0.68)
-0.020 (-0.48)
-0.054 (-0.76)
-0.029 (-0.56)
0.227*** (4.22)
0.240*** (2.65)
0.226*** (4.14)
0.238*** (2.63)
-0.241*** (-13.73)
-0.239*** (-14.95)
-0.029 (-0.24)
-0.027 (-0.33)
0.011 (-1.00)
0.001 (0.14)
-0.030 (-0.25)
-0.010 (-0.09)
0.188*** (3.13)
0.202*** (3.05)
0.029 (0.50)
0.038 (0.77)
0.031 (0.58)
0.038 (0.78)
pur 0.001* (1.69)
0.001 (1.19)
0.001 (1.27)
0.001 (0.87)
-0.001*** (-4.99)
-0.001*** (-4.81)
-0.001*** (-4.25)
-0.001*** (-4.89)
-0.001 (-0.43)
-0.001 (-0.64)
-0.001** (-1.99)
-0.001*** (-3.20)
-0.001 (-1.12)
-0.001*** (-3.55)
-0.000 (-0.39)
-0.001 (-1.30)
0.000 (0.56)
-0.000 (0.59)
0.002*** (3.10)
0.002*** (2.71)
0.001** (2.36)
0.001** (2.34)
floor 0.004 (0.35)
0.010 (1.03)
0.012 (1.37)
0.017* (1.66)
-0.011 (-1.26)
-0.007 (-0.66)
-0.011 (-1.28)
-0.007 (-0.68)
0.061 (-1.30)
0.040 (0.90)
0.072** (2.18)
0.073** (2.01)
0.087* (-1.67)
0.094 (1.40)
0.003 (0.30)
0.006 (0.46)
0.003 (0.22)
0.002 (0.26)
-0.012 (-1.21)
-0.016 (1.46)
-0.009 (-1.07)
-0.012 (-1.01)
ttp -0.006*** (-5.93)
-0.005*** (-5.44)
-0.006*** (-3.22)
-0.004** (-1.98)
-0.003*** (-6.92)
-0.002*** (-3.90)
-0.002** (-2.55)
-0.001 (-0.88)
-0.018*** (-17.76)
-0.022*** (16.54)
0.005*** (2.63)
0.006** (2.01)
0.004 (1.45)
0.007*** (12.75)
0.000 (0.13)
0.000 (0.01)
0.007 (1.56)
0.006 (1.25)
-0.002*** (-2.91)
-0.002** (-2.09)
-0.004** (-2.05)
-0.004*** (-2.79)
tta - - -0.001 (-0.65)
-0.001 (-0.80)
- - -0.001 (-1.50)
-0.001** (-2.08)
- - - - -0.004** (-2.56)
-0.004** (-2.32)
- - -0.007 (-1.52)
-0.006 (-1.19)
- - 0.003* (1.84)
0.001 (1.02)
view - 0.257*** (4.31)
- 0.234*** (3.15)
- 0.227*** (5.62)
- 0.223*** (5.94)
- 0.264*** (4.31)
- 0.042 (0.65)
- 0.027 (0.23)
- 0.247*** (5.22)
- 0.223*** (3.66)
- 0.188*** (4.33)
- 0.207*** (3.50)
ptcapital
- 0.137*** (3.25)
- 0.123* (1.88)
- 0.003 (0.08)
- -0.003 (-0.08)
- 0.006 (0.16)
- 0.075 (1.35)
- 0.109*** (6.51)
- 0.0635 (1.53)
- 0.149** (2.40)
- 0.038 (0.82)
- -0.029*** (-3.53)
coastal_settlem
- 0.029 (0.34)
- 0.040 (0.36)
- 0.087** (2.10)
- 0.095** (2.39)
- 0.127** (2.20)
- 0.090 (1.05)
- 0.249*** (7.25)
- 0.067** (2.12)
- 0.062 (1.27)
- 0.069* (1.73)
- 0.104*** (8.62)
Dimitra Kavarnou - Henley Business School, University of Reading
RESULTS –I Individual Islands• For 33/36 islands the living space is positively very significant to the
prices (1% significance level) while the rest 3 islands (are the islands with
very small sample 15-21 obs)1% increase in living space 0.34-1.07% increase to the prices
( 0.72% increase - weighted average)
• For 21/36 islands the land space is positively (very) significant (1% or 5%)
1% increase in the land area 0.07-0.50% increase to the prices (0.14% increase - weighted average)
• The Property Utilisation Ratio is relatively not significant for most of the islands (gardens/yards not significant – only in 6 islands)
• The floor number is relatively not significant for most of the islands (only in 6 islands)
Dimitra Kavarnou - Henley Business School, University of Reading
RESULTS - II• The property type (flats/detached houses/
maisonettes) seems to be very significant for some of the islands
Detached houses to 14/36 islands negatively very significant (1-5%) compared to flats
i.e. The flats are more expensive compared to detached houses
Maisonettes to 5/22 islands negatively very significant (1-5%) compared to flats
i.e. The flats are more expensive compared to maisonettesMaisonettes to 4/22 islands positively very significant (1-5%)
compared to flats i.e. The flats are less expensive compared to maisonettes –
probably because of their construction/ property characteristics/ extra facilities/ landscape
• The Age is negatively very significant (1-5%) for most of the islands (26/36)
Every Additional Year 0.3-1.4% decrease of house prices
(0.7% decrease - weighted average)
Dimitra Kavarnou - Henley Business School, University of Reading
RESULTS – III
• ViewFor 23/36 islands the view is positively (very) significant (1-5% significance level)Approx. 13.1 – 64.2% more expensive compared to the properties without view (30.2% weighted average)
• Proximity to CapitalFor 7/36 islands the PtCapital is positively (very) significant (1-5% significance level) while for 2/36 islands the PtCapital is negatively (very) significant (1-5% significance level)8/36 Approx. 30.3% (weighted average) more expensive2/36 Approx. 25.2% (weighted average) less expensive
• Coastal SettlementFor 5/36 islands if the property is located in a coastal settlement, it is positively (very) significant (1-5% significance level) Approx. 15.3% more expensive compared to a non coastal settlementwhile for 1/36 islands Coastal Settlement is negatively (very) significant (1-5% significance level)
Dimitra Kavarnou - Henley Business School, University of Reading
RESULTS – VTime Distance to Port:• For the bigger islands (big distances) the time
distance to the port is negatively very significant (1-5%) - the closer to the port, the more expensive (Corfu, Kefallonia, Rhodes)- apart from specific cases (eg. Lesvos)
• For the smaller islands (not very big in size) the time distance to the port was not very significant - apart from specific cases (eg. Paros – Milos – Salamina commuting purposes)
• 11/36 islands showed significance in some of the regressions
Where: 10-13 had negative significance (the less the time - the closer to the port- the more expensive)
While: 3/13 had positive significance (the less the time – the closer to port – the less expensive)
Dimitra Kavarnou - Henley Business School, University of Reading
RESULTS – VITime Distance to Airport:• For some of the islands the time distance to the
airport is positively very significant (1-10%) – the closer to the airport the less expensive - apart from specific cases (eg. Milos) - Probably because of the noise and disturbance.
• 8/22 islands showed significance in some of the regressions
Where: 5/8 had positive significance (the less the time - the closer to the airport- the less expensive)
While: 3/8 had negative significance (the less the time – the closer to airport – the more expensive)
Dimitra Kavarnou - Henley Business School, University of Reading
Thank you